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May 31, 2023 by Colin Dvorak

Microsoft Build 2023, the annual conference for software engineers and web developers, wrapped on May 25th, but the chatter around the event has been going strong all week.

Throughout the event, Microsoft has made more than 50 exciting announcements, with a heavy focus on how AI is reimagining what and how developers build and how it can radically transform the workplace.

Since Microsoft debuted Azure OpenAI late last year, Neudesic an IBM Company, has been focused on developing services and solutions that enable us to support our clients in their AI journey. We’re thrilled with how quickly developments in AI are accelerating. While there is much to get excited about in the coming months, these four announcements stand out.

1. Copilot is coming to Windows 11

Windows will be the first PC platform to centralize AI assistance with Windows Copilot, a personal AI assistant that will be available to use from the taskbar across all Windows apps and programs.

Windows Copilot, which is customizable based on user preferences, can summarize content from apps, explain it or rewrite it, and users can ask questions as well, making it a powerful tool for boosting productivity and completing complex tasks.

A preview of Windows Copilot will start to become available for Windows 11 in June.

2. Bing becomes the default search experience in ChatGPT

ChatGPT will now have the Bing search engine built-in to provide up-to-date answers—grounded by search and web data—directly within the chat.

The new experience, which is already being rolled out to ChatGPT subscribers and will be available on the free tier soon, will also include citations from the web, so users can validate the information and learn more.

3. Azure AI Studio will enable developers to build next-generation AI apps

Azure AI Studio, an integrated no-code platform for OpenAI in Microsoft’s Azure cloud, enables developers to develop, operationalize, evaluate, and deploy AI apps.

With Azure AI tooling, developers can train their own models, ground AI models—such as OpenAI’s ChatGPT and GPT-4—on their own data, create prompt workflows, and more. The Azure AI Studio makes integrating external data sources into Azure OpenAI Service simple and includes built-in support for AI safety.

4. The AI plugin ecosystem is expanding

Microsoft is adopting the same open plugin standard that OpenAI introduced for ChatGPT, enabling interoperability across ChatGPT and Microsoft’s copilot offerings. That means developers can now use one platform to build plugins that work across consumer and business surfaces, including ChatGPT, Bing, Dynamics 365 Copilot, and Microsoft 365 Copilot. They will be able to build experiences that enable users to interact with apps using human language.

Additionally, developers can now integrate their apps and services into Microsoft 365 Copilot with plugins, including ChatGPT and Bing plugins, as well as Teams message extensions and Power Platform connectors. And developers will be able to easily build new plugins for Microsoft 365 Copilot with the Microsoft Teams Toolkit for Visual Studio Code and Visual Studio.

(For details on another exciting announcement on game-changing technology, check out this new blog, Microsoft Fabric 101 & Path to Jumpstart Adoption).

Driving creativity and productivity with AI

We learned so much this week at Microsoft Build, but most of all, we learned that this is just the beginning of the new era of AI. It’s here, integrated into the apps and services we use daily. It will change how we work, enabling us to be more productive than we ever thought possible.

If you are ready to deploy generative AI across your organization, Neudesic offers a range of solutions and services to help you get started, including an OpenAI Jumpstart Workshop that accelerates both the ideation and design of high-value AI use cases. To learn more, contact us today.

Filed Under: Artificial Intelligence, Data & Analytics

March 15, 2023 by Colin Dvorak

Data is the lifeblood of business today, enabling organizations to make quicker, smarter decisions, react to market changes, and better meet the needs of customers.

But that is only if stakeholders across the organization are working with a single source of truth when it comes to data. Far too often, that just isn’t the case. Complex data is being generated by a range of disparate sources, data is siloed, and it becomes nearly impossible for business leaders to get a holistic view of the data or glean any insights they can act on.

Microsoft Dynamics 365 helps bring it all together

Microsoft Dynamics 365 is a suite of interconnected third-party SaaS services and apps that combine customer relationship management (CRM) and enterprise resource planning (ERP) functions.

Through Dynamics, business processes, such as sales and marketing, customer service, finance, and operations, and others are fully integrated and work together seamlessly. It consolidates data from all corners of the organization into a single platform, enabling both analytics and business intelligence that can be used to drive business strategy.

However, for many organizations, getting data out of Dynamics so it can be used effectively across the business can be a challenge.

Data ingestion can slow down momentum

Neudesic, a long-time Microsoft partner, has deployed Dynamics for clients across a range of industries. For some clients—for example, those looking to onboard much-needed software solutions onto Dynamics 365—the process of ingesting data from Dynamics was complex and time-consuming.

“We wanted to help our clients realize the full power of Microsoft Dynamics, and that starts with speeding up that data ingestion process,” says Mike Sherrill, Director of Data & AI at Neudesic. That prompted the organization to design and build a Spark-enabled Dynamics Data Export Connector that directly generates delta tables from CRM Dynamics, and dramatically accelerates the ingestion of Dynamics data. In fact, one large global consulting firm saw a 10X increase in Dynamics 365 data ingestion with the Dynamics Data Export Connector.

For that organization, and many like it, the solution reduces the complexity and time associated with exporting data from Microsoft Dynamics, and provides these benefits:

  • Near real-time data provides insights that enable more accurate and on-time resource management
  • Better data quality and completeness
  • Lower operational costs
  • IT staff now has more time to focus on higher-priority tasks that drive business value

Scenarios & Benefits

Accelerate Data Ingestion
Get data out of D365 quickly and continuously
Select Only Data You Need
Eliminate all unused columns from broad D365 tables
Enrich & Blend Data
Federating and blending with other (external) data
Archive D365
Archiving D365 data to inexpensive Azure DL storage
Enable Analytical Use Cases
Supporting unified data management and analytics for the enterprise
Drive Insights
Bringing insights back into D365

Streamline data management with Neudesic's Dynamics Data Export Connector

The Dynamics Data Export Connector provides you with a simple and effective way to consume data from your Microsoft Dynamics 365 applications to a variety of other platforms, including Power BI, Excel, and SharePoint. With the solution, you can:

  • Automate the data ingest process. You’ll no longer need to manually extract and transfer data between different platforms, saving time and reducing the risk of errors. The Connector also supports near real-time updates, so you can be sure your data is up-to-date and accurate.
  • Configure the solution to meet your needs. Customize the data you ingest and the frequency of ingestion, so you can focus on the data that is most important and use it to drive better decision-making.
  • Have peace of mind, knowing sensitive data is protected. The Connector uses industry-standard security protocols to ensure that data is transmitted safely and securely and that all data is stored in a secure environment.
  • Get up to speed quickly. The solution offers an intuitive interface and is easy to use, even for people with no prior data management experience. The Connector also comes with comprehensive documentation and support, so organizations can get up and running quickly and easily.

 

Unlock the value of your Dynamics data

If you are ready to streamline your data management processes and gain deeper insights into your operations, contact us today. Or click here to learn more about Neudesic’s Dynamics Data Export Connector.

Filed Under: Data & Analytics

March 2, 2023 by Colin Dvorak

Since ChatGPT, a generative AI application, launched in November 2022, we’ve experienced a non-stop hype cycle around the public chatbot that with a few prompts can generate human-like answers.

In the coming months and years ahead, we can expect the hype cycle to continue as more companies roll out and refine alternatives to ChatGPT and OpenAI continues to refine its technology.

In fact, the generative AI market is expected to experience rapid growth in the coming years, as much as 36% through 2032, according to The Brainy Insights, and investor interest has soared. Earlier this year, Microsoft made a multibillion-dollar investment in OpenAI, the research institute behind ChatGPT, and has already vowed to deploy OpenAI’s models across its suite of consumer and enterprise products.

These integrations could be game-changing in the workplace, enabling organizations to unleash unprecedented worker productivity.

But what does that mean for you and your business right now?

In terms of ChatGPT, experts are recommending that you exercise caution for now. You should avoid inputting sensitive or confidential information in ChatGPT. And Bern Elliot, the VP and Distinguished Analyst at Gartner Research, recommends starting with “use cases such as classification, summarization, and text generation for non-customer-facing scenarios.” And he says outputs should be reviewed by a human, at least for now.

Looking forward, though, it’s exciting to think about the impact generative AI can have on individual and team productivity, as Microsoft and other integrations become publicly available.

Here are four areas we think ChatGPT and other OpenAI models will drive individual productivity gains, which will add up and have a positive impact on the business.

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Streamlining online research

In early February, Microsoft announced a new version of Bing and Edge browser, which integrates with ChatGPT, and Google has announced its own generative AI chatbot, Bard, and other generative AI bots are sure to come.

While we’ve had search engines for years, AI-powered searches will enable you to communicate with the chatbot in a human way. You can start with a broader topic, and tell ChatGPT to dig deeper, telling it to be more specific until you get the information you need. This conversational nature allows you to iterate through your search easily and pivot topics as new ideas take shape. Plus, you can often avoid weeding through dozens of irrelevant, often sponsored, ranked articles to locate the precise information you want.

This is promising news for people who spend hours researching online. Tasks like researching competitors or compiling data for a new pitch deck could be reduced , as users are instantly provided with insights they can then validate.

Simplifying email

Microsoft is planning to announce ChatGPT integrations with Outlook, as early as March, which could lead to some serious time savings.

For email, generative AI could dramatically improve search results, bringing an end to the days of scouring through dozens (or hundreds) of emails and long email chains. You could simply search for a specific term or subject, and the AI could offer up a short summary explaining what emails on that subject are about. If you need to dig deeper, you would be able to click on a link to go to a specific email.

It could also summarize lengthy attachments, offering a quick summary and even highlighting key information, making everything from meeting prep to decision-making quicker. “Neudesic is doing a great deal of research in this type of semantic search, and how it can benefit our clients. This would give them the ability to ask a simple question, and then the chatbot searches hundreds of pages and offers this useful summary they can act on,” says Jim Brown, Director of Data Science at Neudesic. “It’s a major time saver, but it also enables stakeholders within an organization to get on the same page, move faster, and make better decisions,” he adds.

Lastly, generative AI could recommend responses to emails in your inbox and even help users create sharper, more professional messages with fewer errors.

Optimizing enterprise resource planning (ERP)

For most businesses, investments in an ERP system, like Microsoft Dynamics, yield quick benefits and ROI. Integrating those systems with generative AI would take the solution to the next level, dramatically improving the speed of data analysis.

For example, generative AI could highlight a customer’s main pain point or complaint and then generate a more custom, response script that better resolves the customer's problem. Or corporate leadership could use it to analyze and summarize vast troves of data for key insights on how to take advantage of financial opportunities and avoid risks.

Delivering better code

ChatGPT has been called a developer’s best friend because it can write simple code and or fix bugs more quickly.

Additionally, integrating generative AI with a solution, such as Microsoft’s Power Platform, could make low-code development even more accessible to users with limited development experience.

With ChatGPT, the natural language-to-code capabilities enable users to articulate what they want the code to do in English, and ChatGPT responds with a function or code snippet. For example, a user could ask it to write a function in Python that will remove outliers from a dataset, and ChatGPT would produce the code, including comments in the code, and an explanation in English of what is happening. Users could then ask it to explain the code in more detail or tell it they meant something else, and the response would evolve. It can also be used to translate between programming languages which is helpful for updating legacy code or generating code in a language the developer has less experience in.

ChatGPT is highly helpful when starting a new project because you don't have to start from scratch. It also manages complex and hard-to-remember syntaxes, like regex, so it could free developers time to focus on more important matters, like improving app quality and performance.

Integrating AI into your business, your questions now answered

Across all these use cases, generative AI offers users the ability to ask questions and receive insights that will inform work and business decisions.

Generative AI offers great promise, and Neudesic could see it significantly boosting productivity and efficiency across many departments. If you’d like to learn more about how AI can benefit your business, we’d love to walk you through it. Learn more.

Filed Under: Artificial Intelligence, Data & Analytics

February 23, 2023 by Colin Dvorak

Heraclitus was not lying when he said, “Change is the only constant in life.”

It doesn’t matter what business or industry you are in. Whether it’s because of new products, processes or people, change is inevitable—and sometimes a pivot must happen overnight. In a world where competition is hot and uncertainties abound, organizations must be able to take quick, decisive action.

Whether organizations are agile enough to do so largely depends on their data strategy—and more specifically, if they can access, learn from—and act on—their data in near real-time.

In a recent post, we talked about the excitement around OpenAI’s ChatGPT and how artificial intelligence (AI) can dramatically boost productivity and efficiency by automating manual, tedious processes. Particularly when it comes to data management, AI can automate data ingestion, preparation, cleansing, visualization, and more. In other words, it acts so you don’t have to.

As the customer success stories below highlight, that automation can be critical for navigating change.

Forced change upends the status quo

One of the most important lessons we’ve learned in recent years is how vital near-real-time data is for resiliency and business continuity. But what if what you need from that data suddenly changes?

For one Neudesic client, major legislation created a need for a brand-new capability. They were suddenly required to identify, redact, and purge information from their records. Without systems to handle this, workers were forced to manually comb through a massive backlog of documents and manually perform these tasks.

These types of problems are best addressed with a combination of Azure Cognitive Services, Custom and OpenAI models to:

  • Automate the identification and extraction of data. Massive repositories of documents are parsed, and sections are redacted automatically or recommended for redaction. The final output consists of entire sections of PDFs that are blacked. Thereby reducing the need for manual intervention.
  • Automate indexing and classification. All documents are classified and categorized. Additionally, stakeholders are able to search documents and find information quickly.

The recent breakthroughs in language models like GPT-3.5 enable new solutions that can navigate disruptive changes, more quickly and efficiently. Neudesic is expanding the use of OpenAI’s large language models to take our Document Intelligence Platform solution to the next level by synthesizing and summarizing the data in ways users can understand and drive actionable insights.

The Neudesic Document Intelligence Platform (DIP) allows non-technical users to apply AI and Intelligent OCR to replace the manual and time-consuming process of extracting data from business documents. Powered by Microsoft Azure AI, DIP can:

Azure Logo
Powered by Microsoft Azure AI
AI to extract data icon
Enable non-technical users to train AI to extract data from any document
Prcess documents icon
Process thousands of documents simultaneously with accuracy
Seemless intration with workflow icon
Be integrated seamlessly into an existing line of business workflow and applications
Firewall icon
Ensure maximum data security measures behind your firewall with Secure AI

Growth requires transformation

For some organizations, like in the previous example, change is forced upon them, requiring them to adapt quickly. However, in most cases, it’s a slow burn to the realization that in order to continue to grow, a shift in strategy is necessary.

For example, Neudesic helped a leading distributor of wholesale pet products take key steps in their digital transformation, including a migration to Azure and e-commerce system deployment. Neudesic also deployed the Document Intelligence Platform on the company’s national enterprise resource planning (ERP) system to transform the organization’s time-consuming, manual invoicing process. The solution automatically:

  • Extracts and stores email invoice attachments
  • Compares invoice data to ERP data
  • Displays comparison information to accounts payable users
  • Creates payment vouchers in the ERP system for invoices that are within tolerance

Now when the company receives an invoice, the Document Intelligence Platform instantly pulls the accurate data, matches purchase orders and receipts, and generates a payment in the ERP system within 30 minutes. Or it flags issues for the accounting team to investigate. The organization is benefiting from a much more streamlined vendor invoicing cycle and has been able to reallocate staff members to more meaningful, higher-value functions.

As—if not more—important, for the first time, the company has an analytics platform in place to measure productivity and efficiency gains. AI is also empowering the company to glean usable insights from its data.

With OpenAI now you can take digital transformation examples like this and evolve them to understand more about language and information and make those insights applicable to your business.

Beyond just capturing data

For years, we’ve been talking about how “organizations are drowning in data but starving for insights.” However, with AI technology, this is no longer the case. By identifying patterns and distilling critical insights, AI can help decision-makers streamline business processes and drive better outcomes. OpenAI's cutting-edge AI capabilities have made this kind of impactful insight automation available to both technical and non-technical users, making companies more resilient, agile, and adaptable to change.

If you’d like to learn how we can help you do the same, contact us today.

Filed Under: Data & Analytics, Digital Transformation

February 16, 2023 by Colin Dvorak

ChatGPT Sprints to One Million usersOpenAI’s ChatGPT was launched in November 2022 and took the world by storm, gaining a million+ users within days – and 100 million users within two months. Then in late January 2023, when Microsoft announced it had invested $10 billion in the tech, the buzz intensified. Stakeholders across all industries are actively working to use this transformative technology to their advantage.

At Neudesic, the 2022 US Microsoft AI Partner of the Year, we’re excited about this next phase of artificial intelligence (AI) and how it can be used to drive efficiency, productivity, and performance for our clients.

What is ChatGPT?

ChatGPT (Generative Pre-trained Transformer), is a public chatbot powered by a Large Language Model (LLM) developed by nonprofit research institute, OpenAI. LLM is part of natural language processing (NLP), the branch of AI which enables us to “talk” to machines. We ask questions and the machine responds like a human would—or at least comes close.

ChatGPT can do that because it was trained on a massive dataset of human-written content on the internet that ends in June of 2021. Therefore, you cannot ask it any current questions but is still extremely valuable. As more people across the globe use it, the more it learns.

ChatGPT isn’t the first of its kind and it won’t be the last. This technology is already being used to automate tasks, including app and software development, marketing and content creation, data management, sales, and more.

OpenAI’s ChatGPT was launched in November 2022 and took the world by storm, gaining a million+ users within days – and 100 million users within two months. Then in late January 2023, when Microsoft announced it had invested $10 billion in the tech, the buzz intensified. Stakeholders across all industries are actively working to use this transformative technology to their advantage.

At Neudesic, the 2022 US Microsoft AI Partner of the Year, we’re excited about this next phase of artificial intelligence (AI) and how it can be used to drive efficiency, productivity, and performance for our clients.

ChatGPT Sprints to One Million users

What is ChatGPT?

ChatGPT (Generative Pre-trained Transformer), is a public chatbot powered by a Large Language Model (LLM) developed by nonprofit research institute, OpenAI. LLM is part of natural language processing (NLP), the branch of AI which enables us to “talk” to machines. We ask questions and the machine responds like a human would—or at least comes close.

ChatGPT can do that because it was trained on a massive dataset of human-written content on the internet that ends in June of 2021. Therefore, you cannot ask it any current questions but is still extremely valuable. As more people across the globe use it, the more it learns.

ChatGPT isn’t the first of its kind and it won’t be the last. This technology is already being used to automate tasks, including app and software development, marketing and content creation, data management, sales, and more.

What makes ChatGPT different than other AI?

AI is not new, and it has increasingly been used in business and industry for a variety of functions to improve productivity and efficiency, customer experience, and decision-making. At Neudesic, we’ve been helping clients successfully scale AI initiatives for years, through our award-winning AI accelerators.

However, what makes ChatGPT different is that non-technical users can use it, and opportunities abound. This generative AI is poised to shake up how companies handle everything from content writing to software development and coding to data science and analytics. For example, Gartner states, “By 2025, 30% of outbound marketing messages from large organizations will be synthetically generated, up from less than 2% in 2022.”

How can you use ChatGPT?

It’s important to note that you cannot just set it and forget it when it comes to ChatGPT, and OpenAI is making that clear.

From OpenAI’s ChatGPT FAQ: “Outputs may be inaccurate, untruthful, and otherwise misleading at times.” And “ChatGPT is not connected to the internet and has limited knowledge of the world and events after 2021, so it could produce harmful instructions or biased content.” In other words, the answers you receive may sound great, but they could be entirely wrong.

So, like most of the experts talking about ChatGPT, we recommend exercising caution. However, we do see ChatGPT as an incredible tool to augment and support your existing operations. We’re excited about the potential benefits it offers, and we see it being used to optimize workflows in these ways:

  • Make sense of staggering amounts of data, by searching for patterns in the content and summarizing findings or offering insights in reports people can easily understand
  • Gain insights in real-time for quicker decision making
  • Develop applications that can analyze data and automate data gathering, cleansing, and formatting
  • Classify and categorize content and data
  • Generate predictive analytics that drives decisions and help organizations avoid risk
  • Automate some customer support functions—like 24/7 responses—and provide a better customer experience
  • Make sales by engaging with potential customers on websites
  • Enable competitive research and customer sentiment analysis on your own business
  • Brainstorm for marketing campaigns, products, initiatives, and strategies

A case for AI—and where Neudesic utilizes large language models

For a leading insurance company, Neudesic implemented its AI-based Document Intelligence Platform, which is built on Microsoft Azure, to automate the processing of 5,000 monthly client accident letters. The documents contain nearly 200 pages that were being manually reviewed, sorted, and data-entered by employees, and the time, cost, and risk associated with the existing process was no longer sustainable.

The Document Intelligence Platform uses AI and machine learning to scan and instantly extract relevant information from those documents and automates the manual error-prone, time-consuming process of extracting data. As a result, the organization received this business value:

  • Reduction in operational costs related to document processing by more than 90%
  • Achieved a 200% increase in efficiency with automation
  • Reduced the overall risk of not meeting expiration dates on demand letters
  • Ensured full data security to remain in compliance

Neudesic is in the process of using OpenAI’s large language model to take our Document Intelligence Platform solution to the next level by synthesizing and summarizing the data in ways users can understand and drive actionable insights.

“At Neudesic, what has us really excited about OpenAI, and all AI for that matter is that it removes many of the tedious, manual, time-consuming processes. It can free people’s time to do the things machines can’t do like think critically, strategize, solve complex problems, lead, and build high-performance teams and workplace cultures. Instead of using people’s time on tasks that can easily be automated, with AI, you unleash them and empower them to do the kind of work that leads to innovation and positive change. Even if we can just make people 20% more productive—and focus that extra time where it matters—imagine what could happen,” says Jim Brown, Data Science Director at Neudesic

If you’d like to learn more about how AI can benefit your business, we’d love to chat. At Neudesic, can provide machine learning and AI capability in weeks—not years. Learn more.

Filed Under: Artificial Intelligence

February 8, 2023 by Colin Dvorak

At Neudesic, we’re committed to partnering with leading utilities companies to accelerate the transition to clean energy and help ensure reliable grid management. We’re working with Microsoft and other technology partners to help utility providers keep the lights on, which has grown more complex and challenging as extreme weather wreaks havoc on aging infrastructure and a rise in electrification pushes the grid to the limits. We want to play a critical role in helping utility providers face these challenges head on and future-proof their organization.

So, on January 31, we pulled together an expert panel to discuss the challenges associated with the clean energy transition and offer practical strategies for moving forward.

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Bilal Khursheed
Director of Energy & Sustainability,
Microsoft Americas

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Kyle Girardi
Manager of Distribution Strategy Development,
Salt River Project

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David Bess
Director of Utilities Innovation,
Neudesic, an IBM Company

While you should absolutely watch the full video, here are some highlights from each of our expert speakers.

We’ve only scratched the surface of putting operation data to work

Bilal Khursheed, Director of Energy & Sustainability, Microsoft America: I've been working with utility providers across North America and the globe, and I haven't come across a single one that doesn't have becoming a “utility of the future” somewhere in their strategic goals. And key industry drivers and challenges are forcing utilities to uncover new value propositions from technology.

Industry drivers and challenges forcing the need to uncover new value propositions from technology

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The good news is that the majority of utilities already have the core data and competencies within their enterprise to enable them to address many of these challenges and capitalize on opportunities by:

  • Transitioning to the cloud
  • Adopting advanced analytics to drive advanced system planning
  • Contextualizing data
  • Aggregating AMI data with weather data for effective load forecasting

Watch the webinar for more insights from Bilal.

More customers + jumps in DER + more electric vehicles WILL impact reliability

Kyle Girardi, Manager of Distribution Strategy Development, Salt River Project (SRP): SRP is one of the nation's largest public power utilities, serving a million+ customers in the greater Phoenix area. We consistently rank high in reliability and customer satisfaction.

However, we are not immune to extreme weather and climate issues. In fact, we hit another peak system record this past year. Our service territory is seeing significant growth in both residential properties and large industry and manufacturing facilities, which will impact our peak load in the future. We also anticipate a 150% jump in customers who have Distributed Energy Resources (DER) and an 800% increase in electric vehicle adoption.

Cleaner Energy Sources for the Future
Each year, SRP steadily adds more clean and renewable energy sources that improve the air quality and help preserve the natural beauty of Arizona.

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Given this growth, we are hyper-focused on ensuring that we can continue to meet our customers’ energy needs and future-proof our distribution system. It’s still early, but our current vision is making sure that we can collect and analyze our data, identify trends, and understand how things are changing—in real time. We have specific goals to meet that objective and are partnering with Microsoft and Neudesic to build a foundational tool that will be central to our goals.

Learn all about SRP’s goals, the solution that will help them become a utility of the future, and where they’re going from here, by watching the full webinar.

The energy transition is dependent on AI

David Bess, Director of Utilities Development, Neudesic, an IBM Company: The grid we have today is, for the most part, not a smart grid. While some utility companies, like SPR, are innovating, what we have now is basically a system that is more than 100 years old. The infrastructure is showing its age. But it’s difficult to balance and optimize the grid in real-time when we have many decentralized energy resources—rooftop solar, electrical vehicles, Building-to-Grid, Vehicle-to-Grid—going on at the same time.

Trying to balance a grid with millions of homes, tens of thousands of transformers, miles of power lines, and all these different devices is extraordinarily difficult. Understanding how people's behavior and consumption patterns change both in the short term (i.e., during the pandemic when many people started working from home) and in the long term is vital. Utility providers need insights to adapt quickly as things change. That ability will be enabled by data and AI, but it will require utility providers to adopt new technologies, like Microsoft Azure, for example.

Neudesic built the Azure Data and AI Platform Accelerator and specifically tuned and optimized it with utilities in mind. Basically, it is a hyperscale data and AI platform that enables providers to get up and running quickly and begin to manage and get value from the massive amount of data that will be coming at them from all these disparate sources. Harnessing that data will be key to helping them navigate the energy transition—and thrive in the future.

Watch the full webinar, “Bold Ideas Powering the Clean Energy Transition”.

Know you’re ready to speak to an expert in utility digitization? Contact us now.

 

Filed Under: Data & Analytics, Digital Transformation

January 23, 2023 by Colin Dvorak

We’ve reached a tipping point—and some experts worry we’ve already surpassed it—where the decarbonization of our energy systems is now urgent if we want to mitigate the climate crisis. And few industries are feeling the urgency like energy and utility providers.

Decarbonization in the industry is critical in and of itself, but maybe even more important, it will enable electrification in other industries. For example, supporting electric vehicles en masse and enabling the migration from gas and oil to electric heat.

The Paris Agreement, legislation, customer demand, and good, old-fashioned self-preservation have prompted energy and utility providers to set lofty net-zero emission targets. In fact, according to a survey by S&P Global Commodity Insights, most leading U.S. utilities have made net-zero commitments:

  • 25 of the country’s 30 largest power and natural gas companies have set interim carbon reduction milestones, two of which have committed to phasing out all greenhouse gas emissions by 2030.
  • Sixteen do not expect to be fossil-free until 2050, a full 15 years past the 2035 goal required under the Paris Agreement on climate change.
  • Only four haven’t set a net-zero emissions goal.

Ultimately, providers realize it’s time to transform the way they operate or miss the mark on the transition to net zero. Still, even as the most innovative companies move forward with their plans, many are finding that while net-zero pledges are easy to make, they are not always easy to deliver.

Keeping the lights on has gotten even harder

The increase in the frequency and severity of extreme weather, coupled with an aging infrastructure and rise in electrification is impacting providers’ ability to offer reliable service. A recent report from Climate Central found that outages have increased by 64% compared with the previous decade.

When service is disrupted, the impact can often go far beyond a few hours of device-less inconvenience for customers. In some cases, a provider’s inability to keep the power on is quite literally a life-and-death situation.

Providers are grappling with how to transform their operations, meet their commitments and boost resiliency—without impacting their customers or diminishing their ability to remain competitive.

New technology adoption creates a whole new challenge

As providers across the globe upgrade their aging infrastructure to combat resiliency issues, they are turning to emerging technology, such as the Internet of Things (IoT), Artificial Intelligence (AI) and Machine Learning (ML), to solve the energy transition conundrum. Such technologies offer providers the ability to:

  • Balance the grid in real time
  • Support distributed energy resources
  • Enable grid automation
  • Determine peak energy times and prevent power outages
  • Forecast and set energy prices
  • Reduce extra energy consumption
  • Improve efficiency and optimize energy supply chain management
  • Identify assets that need to be repaired or replaced—proactively before they cause problems
  • Enable real-time optimization of distribution processes
  • Bolster transparency, accountability, and auditability
  • Keep customers happy
  • Avoid catastrophes

All of which helps the bottom line.

However, while the technologies bring about tremendous benefits, they also create a staggering amount of data.

Most providers simply don’t know what to do with all that data they’re collecting and how to use it to reap the benefits. They can’t find it, easily access it or glean any kind of actionable insights they can use to move the needle on their emissions reduction goals. They’re relying on outdated or corrupted data to make critical decisions with far-reaching impact. Worse, they aren’t protecting their data, leaving the business and customers vulnerable to cyberattacks.

Ultimately, all that data—and sometimes even the technology generating it—is useless without real-time analytics capabilities and a modern data strategy.

So, regardless of where a provider is on the road to net-zero, they may never truly reach the finish line without that critical piece of the puzzle.

Implement a modern data strategy to accelerate the energy transition with Neudesic and Microsoft

Neudesic solutions and Microsoft technologies work together to power a modern data strategy and real-time analytics capabilities. And on January 31 at 10:00 AM PST/1:00 PM EST, experts from both organizations will share their best practices for optimizing, protecting, and managing the energy grid through the power of Data and AI.

You do not want to miss this one! Register now to reserve your spot.

LIVESTREAM
January 31, 2023 - 10AM PST/1PM EST

In partnership with:
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Bold Ideas Powering the Clean Energy Transition

Discover the key role of technology on the path to faster, affordable, resilient,
and secure energy transformation.

Register

Register Now

Filed Under: Data & Analytics, Digital Transformation

December 22, 2022 by Colin Dvorak

This article is Part 3 in a three-part series on scaling AI. If you missed them, you can read Part 1 “How Enterprises Can Scale AI Successfully” and Part 2 “Realizing the Financial Value Of AI” now. And don’t forget to register for our upcoming live webinar on January 31, 2023.

Earlier this year, Microsoft launched the Microsoft Intelligent Data platform, which integrates Microsoft databases, analytics, business intelligence, and data governance products into a unified platform. While Databricks has been instrumental in delivering the cloud-native platform, last month, Microsoft announced that the companies are going even further to evolve the Analytics platform to an open and governed data lakehouse foundation.

That’s great news for existing and future customers, who will now be able to unify their most demanding business intelligence, machine learning (ML), and artificial intelligence (AI) investments.

Understanding the Integrated Solution

The Microsoft Intelligent Data platform is a leading data and AI cloud platform that manages an organization’s data from many disparate sources—and makes it actionable through automation and AI. Foundational to the platform is the Databricks Lakehouse, an open and governed platform that unifies the best of data warehouses and data lakes in one simple platform to handle all data, analytics, ML and AI workloads at scale.

Azure Databricks is tightly integrated with Azure Data Lake Storage, Azure Data Factory, Azure Synapse Analytics, Power BI, and other Azure services.

azure databricks chart

Benefits of Azure Databricks

The strengthened partnership between Databricks and Microsoft “is a significant step forward in helping customers adopt an open, well-governed data lakehouse on Azure with the entirety of the Microsoft Intelligent Data Platform capabilities,” says Ali Ghodsi, Co-Founder and CEO of Databricks. “More than ever, customers are able to quickly and easily unify their data, analytics, and AI with a simple and open approach.”

The platform provides a simple, collaborative environment for data scientists, data engineers, and data analysts to run interactive and scheduled data analysis workloads. But it also enables stakeholders at all levels of the organization to access data—from operational to analytical—and make quicker, stronger decisions, which can impact efficiency, quality, and the bottom line.

Furthermore, because Databricks Lakehouse simplifies enterprise data infrastructure and reduces the need for both a data warehouse and a data lake, organizations can reduce complexity and cost.

Neudesic Quickens Databricks Adoptions

Neudesic, which is a Microsoft 2022 US AI Partner of the Year Winner & Global AI Finalist, is using our Data & AI Platform Accelerator to help organizations quickly deploy a modern data and AI platform.

The solution, built in partnership with Microsoft and Databricks, is built on Databricks Lakehouse and includes pre-built code for integrating data sources, building data models, data governance, and predictive analytics. And we’ve helped organizations—from global manufacturers to large retailers—process, store, clean, share, analyze, model, and monetize vast amounts of data using Azure Databricks. In fact, Neudesic can deploy Databricks end-to-end in 10 days or less.

And don’t forget to register for our upcoming live webinar on January 31, 2023 to discover the key role of technology on the path to faster, affordable, resilient, and secure energy transformation.

Register Now

Filed Under: Artificial Intelligence, Data & Analytics

December 1, 2022 by Colin Dvorak

$30 million. That’s how much one of Neudesic’s manufacturing clients is projected to save with more accurate demand forecasting made possible by artificial intelligence (AI).

How did we do it? To help the manufacturer better understand its supply chain—and take the first step in a calculated approach to modernization—Neudesic quickly stood up a predictive ML model on the Databricks Lakehouse architecture and Neudesic’s Data & AI Platform Accelerator.

The company now has the infrastructure and analytics capabilities in place to optimize the supply chain and deploy a new enterprise resource planning (ERP) system without disrupting the business. And AI has strengthened decision-making across the manufacturing process. Most notably, once Neudesic implemented AI, the client was able to reduce forecasting from a tedious, resource-intensive two+ month process to a mere three minutes.

A powerful use case, for certain, but just one of many examples of how AI is driving transformative change for companies of all sizes across all verticals.

Follow the money—and you’ll find significant investments in AI

If you want a clear sign of the value of scaling AI, look no further than the amount of cash organizations are dumping into it. According to the CIO vision 2025: Bridging the gap between BI and AI, surveyed organizations from the leader group are planning sizeable investments between now and 2025, including:

  • 101% increase in data security spending
  • 85% increase in data governance spending
  • 69% increase in new data and AI platforms and 63% on existing platforms

Why are the top organizations seemingly going all in on AI? It often comes down to data. Organizations are overwhelmed by the sheer amount of data coming at them from all directions, and they are struggling to manage, clean, organize and act on it. In a world where data rules, if you can’t figure all that out, you can fall behind your competitors, bleed revenue through operational inefficiencies, and minimize your profits.

Companies who want to future-proof their business are realizing the importance of investments in AI—and they have high expectations for it. According to the same report, net additions to revenue are expected to be the most tangible form of return gained from AI. And according to Domino Data Lab’s recent REVelate survey, nearly half of respondents expect double-digit growth as a result of data science.

Ranking of the most tangible areas of benefit from AI use today, and expected in 2025.

Can you count on a positive ROI from your AI implementation?

All signs are pointing to “Yes.” Every day at Neudesic, we are helping organizations save money and boost profitability with Neudesic’s Data & AI Platform Accelerator, which is built on Databricks Lakehouse.

One of the biggest challenges our clients—and most organizations face—is that their data is not being used to its full potential. It’s siloed, unsecure, or outdated. Or they simply don’t have the resources to maintain it and analyze it for meaningful business insights. Databricks is foundational to our Data & AI Platform Accelerator because it eliminates all those data silos and dramatically simplifies the data architecture. Once you have visibility into your data—and can actually leverage it—opportunities to cut costs and boost revenues come into view.

How AI is driving profitability

Scaling AI offers the organization-wide visibility and insights needed to surface new opportunities, take calculated risks, cut costs and drive profitability. According to a Deloitte study, the top areas that drive ROI on AI investments include customer service and experience (74%), IT operations and infrastructure (69%), and planning and decision-making (66%).

Upgrading the customer experience. AI, in the form of chatbots, can answer questions 24/7 across the world, in any language, enabling human customer service agents to focus on more complex issues. And while customers do value human interactions, nearly 3/4 of global consumers say they are fine with organizations using AI if it makes life easier. Ultimately, you can help more people. Additionally, AI enables you to act on the massive amounts of customer data you are collecting, offering insights into customer behavior and preferences. With those insights, you can provide more personalization and relevant offers, which can prevent customer attrition, boost loyalty and bolster profits.

Boosting productivity and efficiency. Of all the benefits, this one produces the most tangible results. AI reduces architecture complexity, enables automation, and eliminates manual processes and repeatable tasks. It also dramatically reduces issues and time delays related to human error, so it can be game-changing for IT operations, but the benefits extend beyond the IT team. According to one recent study, AI could boost the productivity of the average knowledge worker by nearly 140%, adding approximately $50,000 in value per worker.

Improving decision-making. AI can analyze tremendous data sets and offer forecasts, predictions, and insights—in real time—a task humans could never do. Plus, the nature of AI means it gets stronger and more accurate with each task it completes, so the models for forecasting and predictions get stronger over time. It basically puts at your fingertips organization-wide visibility and instant access to the information required to make smarter, more calculated, less risky decisions.

Ready to realize the benefits of scaling AI with Neudesic and Databricks?

Interested in learning more about how Neudesic leverages Databricks? Visit our Data & AI Platform Accelerator page to learn more and get in contact with us.

Filed Under: Artificial Intelligence, Data & Analytics

November 3, 2022 by Colin Dvorak

Artificial intelligence (AI) is at the heart of digital transformation (DX), enabling organizations to streamline, operate more efficiently, cut costs and respond more swiftly to ever-changing market conditions.

But deploying AI just for the sake of AI isn’t likely to yield the outcomes most organizations want. For AI to make a meaningful impact, it must be scaled across the organization and embedded in all core business processes and workflows.

If it’s done correctly, that’s where the magic can happen, as organizations gain the real-time capability to harness, clean, and manage their data and glean actionable insights from it that drive smarter business decisions. Scaling AI offers organization-wide visibility, empowering stakeholders throughout the organization to conduct thorough analysis, forecast business outcomes, take full advantage of opportunities, limit risks and drive profitability.

In fact, according to McKinsey & Co. research, companies who scale AI across the organization added as much as 20 percent to their earnings before interest and taxes.

The improvements in operational efficiencies and the bottom line are driving leaders across industries to get serious about scaling AI. Seventy-eight percent of executives surveyed by MIT for the CIO vision 2025: Bridging the gap between BI and AI report—and 96% of the leader group—say that scaling AI and machine learning to create business value is a priority over the next three years.

The leap from PoC to implementation is filled with challenges

As organizations begin to shift from piloting AI technologies to fully operationalizing them, they quickly learn that their legacy systems can’t scale, largely due to a lack of data governance at the enterprise level.

Integraton Pipeline Inforgraphic

Organizations are dealing with a massive amount of data that is growing exponentially and is becoming increasingly difficult to manage, maintain, and clean. Furthermore, the data is nearly impossible to process in real time for vital decision-making. Here’s why:

  • Stakeholders don’t have visibility into the data. Data is siloed across departments and teams and is housed both on-prem and in the cloud.
  • Lack of data standardization. Data is collected from a wide range of sources, and it can become incompatible.
  • Poor data integrity. It is challenging to maintain large sets of data, and it becomes outdated, inaccurate, or corrupted over time.
  • Limited resources. Most organizations simply can’t afford to hire the number of data scientists required to clean and manage all this siloed data, much less analyze it for business insights.

The challenges are too hard for many organizations to overcome, and just a mere 36% of companies are able to deploy an ML model beyond the pilot stage, according to more McKinsey research.

Scaling AI with Databricks and Neudesic

Scaling AI is attainable with the right partner and solutions. To help our clients shed their legacy systems and realize real-time data transformations, Neudesic offers the Data & AI Platform Accelerator which automates the deployment of a single enterprise cloud big data management platform with fully integrated analytics and reporting solutions.

Our solution is built on Databricks Lakehouse, given its unmatched ability to enable our clients to store, clean, and process vast amounts of data.

Infographic - Structured Data to ETL to Data Warehouse to BI & Reports
Infographic - Structured Data to ETL to Data Warehouse to BI & Reports
Infographic - Structured Data to ETL to Data Warehouse to BI & Reports
Inforgraphic - Processing Data using Databricks

Databricks Lakehouse radically simplifies enterprise data infrastructure, reducing the need for both a data warehouse and data lake infrastructure, and it enables stakeholders to access data more quickly and put it to good use. The solution also provides these important features:

  • Support for ACID transactions, which helps to ensure consistency as multiple users concurrently read or write data.
  • Schema enforcement and governance, enabling the platform able to reason about data integrity and provide robust governance and auditing mechanisms.
  • BI support, which enables the use of BI tools directly on the source data to reduce staleness, improve recency and latency, and eliminate the cost of operationalizing two copies of data in a data lake and a data warehouse.
  • Storage is decoupled from compute, so the systems can scale to many more concurrent users and larger data sizes.
  • Open, standardized storage formats and possesses an API, so a variety of tools and engines, including machine learning, can efficiently access the data directly.
  • Support for diverse data types, ranging from unstructured to structured data, is needed for new data applications, including images, video, audio, semi-structured data, and text.
  • Support for diverse workloads, including data science, machine learning, SQL, and analytics.
  • End-to-end streaming eliminates the need for separate systems dedicated to serving real-time data applications.

Ultimately, we chose Databricks to be foundational to the Data & AI Platform Accelerator because we want to empower our clients to leverage their data to do good for their business.

Case in point: When a global rental company wanted to consolidate data that was siloed over five data platforms and make it available for enterprise-wide integration, the organization chose Neudesic to lead the transformation. For the client, the choice was simple because with the Data & AI Platform Accelerator, everything from data ingestion through to the consumption layer is built on Databricks.

Now, the organization will gain near real-time automated data feeds, and stakeholders across the organization will gain visibility into operational metrics. Additionally, the new platform will reduce refresh times on the customer-facing reservation board from 2+ hours to 3 minutes. That’s what Databricks can enable, and it’s why Neudesic makes it integral to our Data & AI Platform Accelerator.

Interested in learning more about how Neudesic leverages Databricks? Register for our webinar in December here!

Resources

Learn more about Data & AI here.

Neudesic AI use case samples:
Leading National Auto Insurance Company
Driving processing efficiency & reducing operational costs by 90% with Neudesic’s Document Intelligence Platform & DPi30.

Leading Multinational Reinsurance Corporation
Driving $3.3M cost reduction & 99% increase in processing efficiency with Neudesic’s Document Intelligence Platform.

Filed Under: Artificial Intelligence, Data & Analytics

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